SPAN, consisting of Dr. Matias del Campo and Dr. Sandra Manninger is a team of architects from Vienna, Austria. Their architecture is characterized by a combination of advanced techniques and philosophical inquiry interrogating the ontological and epistemological framework that produces a paradigm concerned with advanced technology as an agent of culture. The work covers the range from text, installations, industrial design to buildings and urban concepts. The diverse oeuvre can be found in public collections (MAK, Albertina, Pinakothek Munich, FRAC) as well as in private collections (Benetton, Alessi). In 2010, SPAN and Arkan Zeytinoglu designed the architecture and the interactive concept of the Austrian Pavilion for the Expo in Shanghai, which subsequently resulted in numerous built projects for the Asian region. In 2014, Matias del Campo and Sandra Manninger accepted the call from the University of Michigan to join the faculty of Taubman College. In close cooperation with the Faculties of Robotics and Computer Science at the University of Michigan, SPAN developed new design methods for architecture based on Artificial Intelligence. The Robot Garden, for Michigan Robotics is the first built project using Generative Adversarial Networks (GAN’s) as design method.
The work of SPAN is presented by both partners internationally in numerous lectures and exhibitions. The work has been shown at the Venice Architecture Biennale, the Vienna Biennale, Beijing Biennale, Buenos Aires Biennale, Tallin Biennale, the Austrian Cultural Forum NY, and at the Archilab 9, FRAC Orleans. Solo exhibitions were shown at the MAK Vienna and the FAB Union Gallery in Shanghai. Numerous publications, either as author or editor, support and explain SPAN’s theoretical position. These range from interviews and essays to scientific articles. The AD (Architectural Design, Wiley, London) edition Evoking through Design was designed by Matias del Campo and the book Sublime Bodies was published by Tongji Press. The book Neural Architecture, which presents SPAN’s theory on artificial intelligence and cultural production, will be published in 2021.
Urban Fictions is an experiment in exploring the combination between patterns created and curated by SPAN and urban textures of existing cities. In short, SPAN’s renderings serve as the target image, and satellite images of selected cities serve as the originals, producing images that oscillate between tangible realism and unlikely scenarios. This thin line between utopia and reality is precisely what makes these images a compelling proposal for a re-evaluation of the urban condition. Urban Fictions can also be read as a response to the current criticism of the city in the light of the current Covid-19 crisis. Instead of joining the choir praising life in the countryside as a remedy in times of social distancing, Urban Fictions celebrates urbanity and its density as a possible, or rather necessary, future. The reasons why could fill tomes, but in short: architects understand that the city is (apart from being a symbol of human culture) a necessity when it comes to the responsible consumption of the planet’s resources. Instead of painting a gloomy dystopia (controlled by a pathogen), Urban Fictions relies on the possibility of lauding urbanity and advocating for a re-evaluation of the city with the aid of machine learning.
It should be stated that this is only a first attempt in the area of the critical examination of planning in architecture in the age of AI. In fact, there is still a lot to be done. The results of this paper can only be seen as an initial effort at tapping into the potentials of this approach, which could range from novel design directions that look at how machines see our world (with all the wonderfully strange results in terms of morphologies, chromatics, and possible theories) to profoundly pragmatic approaches. Further research needs to be done to dive deeper into the opportunities presented by this approach to urban design. In that sense, the work on this problem can be considered a work in progress. The refinement of the algorithm allows for continuing the conversation laid out in this design methodology. We have already begun to refine this approach and to expand the code to understand the semantic information, crucial for a well-informed design method, and we are looking forward to the in-depth exploration of this posthuman design ecology. (Read the entire text in the upcoming edition of IAAC-Bits, published by ACTAR, Barcelona)
THE ROBOT GARDEN
Architecture has rarely found points of intersection with the research conducted on Artificial Intelligence on a global scale. Even today, the discussion of AI and Architecture has barely started. Considering the enormous potentialities of this area of research regarding its application in architecture, it is more than strange that this has not been discussed in wider circles within the discipline. In recent years we have seen rapid development in the progressive methods emerging from AI research, resulting in applications that surround us continuously. Almost undetected, AI applications have seeped successfully into our daily life: voice recognition, ride-sharing apps, banking apps, face recognition, AI Airline Pilots, smart home devices, and more, are already naturally ingrained into our environment. More are in the pipeline that reaches from AI-driven Cars to farming with intelligent machines. The possibilities of these methods will transform all areas of our daily life and will mutate the planet.
SPAN (Matias del Campo & Sandra Manninger) have been in touch with AI experts since the late 90ies when they first came in touch with the faculty of the OFAI, the Austrian Institute for Artificial Intelligence. One of the oldest of its kind, it was founded in 1969. These early meetings provided a basis for understanding the potentialities of this area of research, it was however the input by the Robotics Institute of the University of Michigan that turned out to be a game-changer. After almost a year of conversations and experiments, the Robotics Institute offered SPAN the chance to design the Robot Garden, based on 2D to 3D Style transfer techniques that were specifically geared towards architecture design. What is the Robot Garden, you ask? First and foremost, it is a testing facility for robots. Michigan Robotics has specialized in exploring the possibilities of Bipedal Robots. Robots on two legs. Combining its expertise in Machine Vision and Machine Learning, the team around Director Jessy Grizzle has made essential steps forward in the development of bipedal robots. These robots are designed to operate in areas normally designed for humans, such as factories, and in uneven terrain – think of the farming example mentioned above. In order o test these abilities, a testing ground was conceived, right next to Robotics’ new facility, the University of Michigan Ford Robotics Building. The outline given to SPAN called for a Robot Garden that contains a set of different terrains, from sand to grass to gravel, to rockface. Inclinations and steps were part of the catalog of features that were desired in order to interrogate the “last 50 feet” problem. (Read the entire article in Antagonismos Magazine No.6 2020)
21 HIGHSCHOOL SHENZHEN – CHINA
When Walter Gropius, at the beginning of his career, started to work in Peter Behrens office, he kept a terrible secret: he could not draw. He struggled with this deficiency in the environment of the Behrens office but famously became proficient in dictating drawings to his collaborators, demonstrating the ability of language to describe the complex material and spatial relationships in an architectural project. Synonymously Sol LeWitt expanded the concept of description into an entire career, dedicated to the efficacy of language (as instructions) and foreshadowing the emergence of programming and scripting as a means of artistic and architectural expression. So, what is the relationship of language to architecture?
The motivation to explore Attention Generative Adversarial Networks (AttnGAN) as a design technique in architecture can be found in the desire to interrogate an alternative design methodology that does not rely on images as a starting point for architecture design, but language. Traditionally architecture design relies on visual language to initiate a design process, whether this be a napkin sketch or a quick doodle in a 3D modeling environment. AttnGAN explores the information space present in programmatic needs, expressed in written form, and transforms them into a visual output. This visual output can be further processed into three-dimensional models that transport lingual information into fully developed architectural entities. The key results of this research are shown in this paper with a proof-of-concept project: the competition entry for the 24 Highschool in Shenzhen, China. This award-winning project demonstrated the ability of GraphCNN to serve as a successful design methodology for a fairly complex architecture program. In the area of Neural Architecture, this technique allows interrogating shape through language. An alternative design method that creates its own unique sensibility. In the project we demonstrate how this method is able to subdivide larger volumes of the program, resulting in discrete chunks and volumes that possess an inherent compositional quality, albeit a nonhuman one.